Improvements in the efficiency of linear MPC

Shuang Li; Basil Kouvaritakis; Mark Cannon

doi:10.1016/j.automatica.2009.10.010

Improvements in the efficiency of linear MPC

Shuang Li, Basil Kouvaritakis^*, Mark Cannon

^*Corresponding author for this work

University of Oxford

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

A model predictive control (MPC) strategy based on augmented autonomous predictions enables a highly efficient online optimization by imposing a terminal constraint at the current time. Near-optimal performance is obtained by delaying the imposition of the terminal constraint by one sampling period. However, under certain conditions the degree of optimality can be affected. An extension is proposed to remove this difficulty, yielding significant improvements in the degree of optimality, and achieving this at modest computational cost.

Original language	English
Pages (from-to)	226-229
Number of pages	4
Journal	Automatica
Volume	46
Issue number	1
DOIs	https://doi.org/10.1016/j.automatica.2009.10.010
Publication status	Published - Jan 2010
Externally published	Yes

Keywords

Constrained control
Optimization
Predictive control for linear systems

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10.1016/j.automatica.2009.10.010

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KW - Predictive control for linear systems

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Improvements in the efficiency of linear MPC

Abstract

Keywords

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